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The Logistics of Scientific Growth in the 21st Century

Over the last few months, I’ve noticed a growing number of reports about declining opportunities and increasing pressure for early stage academic researchers (Ph.D. students, post-docs and junior faculty). For example, the Washington Post published an article in early July about trends in the U.S. scientific job market entitled “U.S. pushes for more scientists, but the jobs aren’t there.” This post generated over 3,500 comments on the WaPo website alone and was highly discussed in the twittersphere. In mid July, Inside Higher Ed reported that an ongoing study revealed a recent, precipitous drop in the interest of STEM (Science/Technology/Engineering/Mathematics) Ph.D. students wishing to pursue an academic tenure-track career. These results confirmed those published in PLoS ONE in May that showed the interest to pursue an academic career of STEM students surveyed in 2010 showed evidence of a decline during the course of Ph.D. studies:

Figure 1. Percent of STEM Ph.D. judging a career to be “extremely attractive”. Taken from Saurman & Roach (2012).

Even for those lucky enough to get an academic appointment, the bad news seems to be that it is getting harder to establish a research program. For example, the average age for a researcher to get their first NIH grant (a virtual requirement for tenure for many biologists in the US) is now 42 years old. National Public Radio quips “50 is the new 30, if you’re a promising scientist.”

I’ve found these reports very troubling since, after over nearly fifteen years of slogging it out since my undergrad to achieve the UK equivalent of a “tenured” academic position, I am acutely aware of the how hard the tenure track is for junior scientists at this stage in history. On a regular basis I see how the current system negatively affects the lives of talented students, post-docs and early-stage faculty. I have for some time wanted to write about my point of view on this issue since I see these trends as indicators of bigger changes in the growth of science than individuals may be aware of. I’ve finally been inspired to do so by a recent piece by Euan Ritchie and Joern Fischer published in The Conversation entitled “Cracks in the ivory tower: is academia’s culture sustainable?“, which I think hits the nail on head about the primary source of the current problems in academics: the deeply flawed philosophy that “more is always better”.

My view is that the declining opportunities and increasing malaise among early-stage academics is a by-product of the fact that the era of exponential growth in academic research is over. That’s nonsense, you say, the problems we are experiencing now are because of the current global economic downturn. What’s happening now is a temporary blip, things will return to happier days when we get back to “normal” economic growth and governments increase investment in research. Nonsense, I say. This has nothing to do with the current economic climate and instead has more to do with long-term trends in the growth of scientific activity over the last three centuries.

My views are almost entirely derived from a book written by Derek de Solla Price entitled Little Science, Big Science. Price was a scientist-cum-historian who published this slim tome in 1963 based a series of lectures at Brookhaven National Lab in 1962. It was a very influential book in the 1960s and 1970s, since it introduced citation analysis to a wide audience. Along with Eugene Garfield of ISI/Impact Factor fame (or infamy, depending on your point of view), Price is credited as being one of the founding fathers of Scientometrics. Sadly, this important book is now out of print, the Wikipedia page on this book is a stub with no information, and Google books has not scanned it into their electronic library, showing just how far the ideas in this book are out of the current consciousness. I am not the first to lament that Price’s writings have been ignored in recent years.

In a few short chapters, Price covers large-scale trends in the growth of science and the scientific literature from its origins in the 17th century, which I urge readers to explore for themselves. I will focus here only on one of his key points that relates to the matter at hand — the pinch we are currently feeling in science. Price shows that as scientific disciplines matured in the 20th century, they achieved a characteristic exponential growth rate, which appears linear on a logarithmic scale. This can be seen terms of both the output of scientific papers (Figure 2) or scientists themselves (Figure 3).

Figure 2. Taken from de Solla Price 1963.

Figure 3. Taken from de Solla Price 1963.

Price showed that there was a roughly constant doubling time for different forms of scientific output (number of journals, number of papers, number of scientists, etc.) of about 10-15 years. That is, the amount of scientific output at a given point in history is twice as large as it was 10-15 years before. This incessant growth is why we all feel like it is so hard to keep up on the literature (and incidentally why I believe that text mining is now an essential tool). And these observations led Price to make the famous claim that “Eighty to 90 per cent of all the scientists who have ever lived are alive now”.

Crucially, Price pointed out that the doubling time of the number of scientists is much shorter than the doubling time of the overall human population (~50 years). Thus, the proportion of scientists relative to the total human population has been increasing for decades, if not centuries. Price makes the startling but obvious outcomes of this observation very clear: either everyone on earth will be a scientist one day, or the growth rate of science must decrease from its previous long-term trends. He then goes on to argue that the most likely outcome is the latter, and that scientific growth rates will change from exponential to logistic growth and reach saturation sometime within 100 years from the publication of his book in 1963 (Figure 4):

Figure 4. A model of logistic growth for Science (taken from de Solla Price 1963).

So maybe the bad news circulating in labs, coffee rooms and over the internet is not a short-term trend based on the current economic downturn, but instead reflects the product of a long-term trend in the history of science? Perhaps the crunch that we are currently experiencing in academic research now is the byproduct of the fact that we are in Price’s transition from exponential to logistic growth in science? If so, the pressures we are experiencing now may simply reflect that the current rate of production of scientists is no longer matched to the long-term demand for scientists in society.

Whether or not this model of growth in science is true is clearly debatable (please do so below!). But if we are in the midst of making the transition from exponential to logistic growth in science, then there are a number of important implications that I feel scientists at all stages of their careers should be aware of:

1) For PhD students and post-docs: you have every right to be feeling like the opportunities in science may not be there for you as they were for your supervisors and professors. This message sucks, I know, but one important take-home message from this is that it may not have anything to do with your abilities; it may just have to do with when you came along in history. I am not saying that there will be no opportunities in the future, just fewer as a proportion of the total number of jobs in society relative to current levels. I’d argue that this is a cautiously optimistic view, since anticipating the long-term trends will help you develop more realistic and strategic approaches to making career choices.

2) For early-stage academics: your career trajectory is going to be more limited that you anticipated going into this gig. Sorry mate, but your lab is probably not going to be as big as you might think it should be, you will probably get fewer grants, and you will have more competition for resources than you witnessed in your PhD or post-doc supervisor’s lab. Get used it. If you think you have it hard, see point 1). You are lucky to have a job in science. Also bear in mind that the people judging your career progression may hold expectations that are no longer relevant, and as a result you may have more conflict with senior members of staff during the earlier phases of your career than you expect. Most importantly, if you find that this new reality is true for you, then do your best to adjust your expectations for PhD students and post-docs as well.

3) For established academics: you came up during the halcyon days of growth in science, so bear in mind that you had it easy relative to those trying to make it today. So when you set your expectations for your students or junior colleagues in terms of performance, recruitment or tenure, be sure to take on board that they have it much harder now than you did at the corresponding point in your career [see points 1) and 2)]. A corollary of this point is that anyone actually succeeding in science now and in the future is (on average) probably better trained and works harder than you (at the corresponding point in your career), so on the whole you are probably dealing with someone who is more qualified for their job than you would be. So don’t judge your junior colleagues with out-of-date views (that you might not be able to achieve yourself in the current climate) and promote values from a bygone era of incessant growth. Instead, adjust your views of success for the 21st century and seek to promote a sustainable model of scientific career development that will fuel innovation for the next hundred years.

50 thoughts on “The Logistics of Scientific Growth in the 21st Century”

Thanks for the interesting blog post. So in your opinion what determines the “carrying capacity” of scientists in society — what is causing the transition from exponential to logistic growth at this particular level?

Another thought — the leveling off of the number of scientists is going to have to cause a change in how science is done. Right now scientific productivity of labs depends on lots of cheap labor (undergrads and grad students work hard and don’t cost much), but then there is nowhere for them to go (in academia anyway) when they graduate. Scientific productivity requires lots of scientists-in-training, but doesn’t give them anywhere to go after the training is done. If we reduce the number of scientists, we need to reduce the number of scientists-in-training, and then the productivity of many labs would grind to a halt.

The solution has to come from a different way of doing science altogether that does not depend on a cheap-labor pyramid scheme.

Excellent question. I don’t think this question has an easy answer, but I would guess that it lies somewhere more towards the demand to train people for white-collar jobs in the information economy, than the need to develop new technologies to improve human welfare. Clearly, if there is indeed going to be reduced growth in the number of scientific jobs in the future, then answering the “carrying capacity question” is the key thing to making good projections.

I’m not so sure that I agree, however, that science will grind to halt if we reduce the cheap labor pool. Surely some forms of “work harder, not smarter” science will suffer, but these are probably areas where most trainees are treated as technicians anyways, so the real outcome of these changes on the number of scientists placed in academia will not change much. The real reason I disagree with the idea that productivity will suffer if we slow the system down is that this idea is based a notion that equates productivity with growth. I am confident we can design systems where we give fewer scientists more time do real science that would lead to a better outcome for all.

Nice! This is a very interesting debate.
Price could not have forecasted the possibility that technology would one day allow for open universities (e.g. Udacity) that can reach out to the millions. But I guess you are arguing for logistic growth within the “walls” (so to speak), which is hard to disagree. So, outside of that, one could easily see that there will be a continued increase in the number of non-institutional-scientists worldwide regardless of regional economic downturns that will produce many new opportunities than ever before. The main driving force is that there are too many real-world problems to be solved. It is good to see that at least some of the univs./institutions are already starting to rethink/restructure and become flexible in step with the changing society and the market place. Thanks for the post!

Great point. I was implicitly assuming the number of scientists within the ivory tower. I fully agree that there will be a larger number of citizen scientists contributing to discovery this century (as was more common in the 19th century) and welcome this transition and mechanisms to enable it. One cool idea I’ve seen lately is the Ronin Institute (http://ronininstitute.org/), which is a collective of researchers who are not affiliated with Unviersities that seems to be filling a gap created by the crisis in higher education we are discussing here. I encourage readers to have a look at their mission statement here: http://ronininstitute.org/mission/

Very good post. We do not agree with you, but we are thankful that you are able to take the debate to higher level than staying stuck with the conventional wisdom – “The problems we are experiencing now are because of the current global economic downturn. What’s happening now is a temporary blip, things will return to happier days when we get back to “normal” economic growth and governments increase investment in research.”

Very nice post – I agree that this is unlikely a temporary blip based on current economics. Going forward it would help at least some if entering grad students are realistic, and departments are honest, about job prospects. And if departments aren’t seeing their grads get permanent positions in either academia or somewhere else doing science, they’ll need to adjust their training to change that or lose out on talented students.

Thanks Jesse. I agree that increased realism for incoming trainees is crucial. But I should hope a realistic message doesn’t hurt the recruitment of good talent. Otherwise we’d fall back into the trap of using false expectations as bait to hook the next generation of scientists.

The problem is that everyone believes themselves to be the exception. I show data to incoming recruits from the survey of doctorate recipients and the the recent NIH working group, but my sense is that most students believe they can beat the odds.

Hi Casey, nice post. Sometimes it feels like we’ve already reached saturation, though I’m not sure how you’d going about measuring it. The De Solla books are great, Science Since Babylon is worth a read too (if you haven’t already) – although out of print, they are available in all good libraries e.g. http://www.library.manchester.ac.uk/ etc

Are we seeing the transition of growth for science from exponential to logistic?
Perhaps at a national level in countries with long tradition of supporting research? OTOH: higher ed and research is still a pre-industrial guild type craft with apprentices, journeymen, masters.

Excellent post, Casey! I hadn’t heard of De Solla Price before reading this post. So mission accomplished!

DSP and Kuhn were contemporaries, right? I anticipate that paradigm shifts will be even harder under a logistic growth regime for two reasons. First, the self-inflicted brain drain is chasing away promising, cross-pollinating Young Turks. Second, the stultifying competition for dwindling resources among the graying establishment that remains behind doesn’t strike me as a climate hospitable for bold creativity.

I’ve bemoaned the mentorship vacuum on Twitter and elsewhere. The upwelling of self help and group therapy that’s currently sweeping across the science blogosphere is a warm salve for the cold indifference of the tenuriat, though there certainly are courageous and well-meaning PI’s out there, if you’re lucky enough to connect with them.

Like you, I see this as the first wave of attrition that will redistribute scientific talent out of universities and into independent research institutes, consortia, startups or other creative, technical sectors.

I know there a lot of recently or imminently tenured profs who desire to change the system but I’m not optimistic that they’ll be able to get around obstructionists in the ranks of senior academics. Some external shock is going to have to occur to really spook the white beards, because the slow-motion train wreck of the last decade hasn’t caused them to bat an eyelash.

I agree that, at some point, the numbers of scientists are going to taper off/asymptote – but I’m not sure that we have genuinely reached that point yet. A rather large confounding factor that I think is “artificially” choking off the growth of science budgets and science jobs is the overwhelming influence of market fundamentalism/neoconservatism, which has seen governments become less and less willing to invest in anything that might be viewed as a public good, and, at the same time, demanding more and more “evidence” of productivity and efficiency from academics (and anyone else in any form of the public service). I’m in the early stages of an academic career in Australia and finding it exceedingly difficult to get established (I’m also finding the expectations placed on me are growing at an exponential rate and becoming more and more surreal every year). In 1996, a newly elected government basically went on a vendetta against universities and the public service in general and made it a priority to remove as much funding as possible from the higher education and research system. At the same time, they increased the administrative reporting and compliance demands and went out of their way to undermine the entire higher education sector. This government has since been voted out but their successors have shown no inclination whatsoever to put any further investment into public research in Australia. The money is there (even with the reduced budgets of the global financial crisis) – but the government refuses, for what seem to be market ideological reasons, to put any real funding into universities or other public research. It’s not a lack of available money, it’s simply a succession of Australian state and federal governments that believe that universities and research should not be publicly funded.

Given that the number of university students has continued to increase (close to exponentially, I think), during this same period of time, while the number of researchers and the available grant money has pretty much stagnated (staff to student ratios in Australia have roughly doubled since 1996), I suspect that the confounding influence of market fundamentalism may have a lot more to do with the slow down in science spending than any “natural” transition from exponential to logistic growth in science. At least in Australia.

That’s exactly applies to Spain, with a conservative gov literally fighting against scientists. Anything smelling like progress, auto-criticism, public welfare is blocked. It starts with first grade education, it culminates with ridiculous funding allocated to science. There is no political will. We are alone. Brain drain was easy years ago, not now. The academic ranking system must change to accommodate scientists. We are not only facing a drastic overall crisis, we are facing a market conservative agenda which does hate progress, in terms of human development. I see the point of this article, but in my humble opinion the belligerence of ruling parties against science has consequences.

I agree completely. There are those who say that we have hit some sort of “inventive glass ceiling” where all the low-hanging fruit has already been exploited. But the previous generation probably said the same thing. After all, once you invent the lightbulb where can you go? The point is that they didn’t know and we don’t know.

Sure, theoretically, there could come a time when we know all there is to know or a time the rate of discovery will slow down on its own accord (not due to external forces). Personally, I think we are more than likely to be an extinct species before we hit that wall.

However, one thing is certain, when you choke off funding for discovery, discovery will slow down and eventually stop. Poor and short-sighted policy has created this, not some imagined technical wall. And there is plenty of blame to go around. In the US, funding for the NSA and NIH have been choked off by anti-science conservative extremists. But senior scientists are also to blame. They’ve become addicted to cheap labor in the form of limitless supply of graduate students and post-docs. This has fueled the problem by creating a gut of Ph.D.’s.

We are also now seeing the results of such short-sighted policies with respect to public health. Look at how botched the initial response to the first Ebola patient was in the US. You can’t keep cutting budgets and have one person doing the job of four people and expect a smooth operation.

How does this relate to decolonialization? There’s a huge fraction of the human race who were guaranteed to be unavailable to compete in science until the 1970s, since their parts of the world were parts of global systems that relegated them to primary resource production?

Now we have Indian scientists, Chinese scientists, a lot more South American scientists — and even a few Africans involved. If we want to understand the nature of the “science labor market”, we have to at least consider the effect of all these new scientists competing with the old protected European scientists, in addition to the creation of whole new markets to practice science in (India, China, S. America…).

Great post. Quite a bit to chew on here. First, what do the numbers (of papers/abstracts published, scientists produced, etc.) look like post-1963? Does the trend hold true with the model? Second, although it makes intuitive sense, is the output of scientific abstracts/papers really the best measure of scientific “growth?” Looking forward to reading your thoughts.

I think the salient point here is that there IS a “carrying capacity” for amount of science/scientists in society. My question is: what determines that point? The answer seems clear to me: it’s the amount society is willing to invest in science. Right now, scientific spending in the Western world is a measly fraction of most country’s total spending, especially when compared to Defense spending. If we move some of these other expenditures into science over time, I believe that not only would we once again see the exponential growth in science and the opening of many opportunities for scientists, but a fundamental shift in culture towards one of increased scientific literacy, innovation, and technological progress.

Excellent post – and impressive resurrection of the out-of-print ideas of de Solla Price and his graphs. The signs have been there for a number of years but have been obscured by a number of factors (largely one-offs). These include the economic turmoil, the extension of both PhDs and postdocs (each of which have been stretched to temporarily accommodate the dearth of opportunities), the injections of short terms funds (TARP in the US), technological changes and larger labs. The receptor capacity of the private sector in life sciences has also been reduced by the consolidation of pharma as well as the closing of early research facilities. These elements will likely result in a hard landing for many (those who cannot turn back the clock). The chilling effect on new students is already apparent (as in the first graph). Add to this the increasing expectations of the public and governments, the trends to smaller government and the move by health charities towards “cure” promise research (often based on over-selling by people who should know better) and confidence in science is likely to be reduced exactly at the time when investment in new science should be helping to power us out of recession.

A most stimulating post. There is doubtless a carrying capacity for science, as for any cultural activity. While some countries may be close to that point, many others are not. So it boils down to “have PhD will travel and engage in adventure”. Why stay close to home? Success inside the ivory tower may be linked to mobility – anyone have any data on that? My department is one third non UK origin and it rocks, as well as speaking many languages and knowing many cuisines!

@balapagos touches on a key point. I have argued (though not in writing) that in a truly civilised society, everyone will at some point have the time and resource to undertake a degree in the field of their choice; a good many may then do a research degree. This ensures that we would indeed by “ruled by philosophers” and live in a more enlightened world.

Reblogged this on Shane O'Mara's Blog and commented:
A brilliant and sobering post on the future for scientific growth – there is a long-term, secular trend in growth that drives change, independent of how we might otherwise wish things to be. And perhaps also this might be an opportunity? Accepting that there are demographic, economic and other long-term trends that will limit the traditional growth of science means we need to start thinking hard about other ways of training the scientifically-minded of the future, for the new careers that do not yet exist, but which deviate from the traditional model.

“either everyone on earth will be a scientist one day, or the growth rate of science must decrease from its previous long term trends”

Which one do you prefer? Everyone can be a scientist to a degree they want to be. The only argument for reducing the proportion of scientists is that there is not enough money to fund them all. Actually there is plenty of money – over $140 billions of federal annual R&D spending in the US alone – but the current funding system is pervevse and extremely wastefull. By some estimates up to 85% of all research funding is wasted, over 50% of publications are not reproducable.

Everyone should have a fair shot at pushing the edge of unknown, in a reproducable way. Be it a 14 year old, who finds that stevia sweetener is an insecticide, or a freshly minted PhD who has some bright but risky idea. Currently, these people can’t get funding – they have to “serve” masters, who have access to all the funding, over half of which goes to their university coffers as “overhead” waste. Only some fraction trickles to postdoc and research assistant salaries with all the associated overheads and taxes. Why so much waste?

We have to fundamentally rethink how science funding is distirubted. Reward directly those that deliver reporucable results. Anything else, be it degrees, prestige, preceived importance, or how many program officers one knows at NSF or NIH should not matter at all.

Casey, I’ve long had similar, although rather less-well formed ideas about the same problem. I also completely agree with you about the current scare stories in the media, which are out of touch. My students and my academic grandchildren should all be made aware of the situation.

Let’s not forget the inevitable outcome of a system where exponential growth is no longer in effect: each tenured professor/PI will get to train ~one person to take their place as a tenured professor/PI over the extent of their entire career. At high profile institutions, they will probably get to train a few, but that means researchers at other institutions will never get the chance. That is a fundamental difference, so how does that change the system?

I agree with many of the comments here. This is a huge debate within the scientific community and we kind of know and agree on the solutions. I think regarding the exponential growth of the number of scientists, the maximum theoretical number of people is the proportion of the population that want to be scientists. The process for producing scientists should work to filter out those not capable of scientific work. The competition should be for who gets to answer what questions. Resources should ideally be distributed based on how much it costs to generate those answers.

I assume there is a large percentage of people who would be scientists, if everyone could be whatever they want. The carrying capacity is the economic demand for scientists. How much of our economic resources are devoted to scientific knowledge creation? I would argue at least as much as devoted to healthcare, education, or “defense”.

The problem, as others have noted, is political. Governments around the world need to step up their games in terms of funding, in order to absorb the entire supply of produced scientists. I think the historical contingency of one country, the U.S., having the greatest demand for scientists has led to a culture that is very much international. This is potentially a huge advantage, because we have a world-wide network of people willing to move anywhere for work, and a culture that encourages them to do so. Countries should compete to attract the best scientists by competing to provide the most funding.

Thanks for this post, de Solla Price’s work is very relevant today and isn’t discussed enough. I was interested in this question and did an analysis of PhD’s granted, patents granted, and papers published worldwide since 1900, and I haven’t found any evidence of a slowdown — it’s true that the US and UK might be reaching the saturation point, which can be frustrating for people in academic jobs here, but the slack is being picked up by China.